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Cryodamage affects the normal physiological functions and survivability of boar sperm during cryopreservation. Lysine acetylation is thought to be an important regulatory mechanism in sperm functions. However, little is known about protein acetylation and its effects on cryotolerance or cryodamage in boar sperm. In this study, the characterization and protein acetylation dynamics of boar sperm during cryopreservation were determined using liquid chromatography–mass spectrometry (LC-MS). A total of 1440 proteins were identified out of 4705 modified proteins, and 2764 quantifiable sites were elucidated. Among the differentially modified sites, 1252 were found to be upregulated compared to 172 downregulated sites in fresh and frozen sperms. Gene ontology indicated that these differentially modified proteins are involved in metabolic processes and catalytic and antioxidant activities, which are involved in pyruvate metabolism, phosphorylation and lysine degradation. In addition, the present study demonstrated that the mRNA and protein expressions of SIRT5, IDH2, MDH2 and LDHC, associated with sperm quality parameters, are downregulated after cryopreservation. In conclusion, cryopreservation induces the acetylation and deacetylation of energy metabolism-related proteins, which may contribute to the post-thawed boar sperm quality parameters.

Portable interfaced robot arms equipped with mobile user interactions are significantly being utilized in modern world. The application of teaching robotics is being used in challenging pandemic situation but it is still challenging due to mathematical formulation. This article utilizes the augmented reality (AR) concept for remote control-based human-robot interaction using the Bluetooth correspondence. The proposed framework incorporates different modules like a robot arm control, a regulator module and a distant portable smartphone application for envisioning the robot arm points for its real-time relevance. This novel approach fuses AR innovation into portable application which permit the continuous virtual coordination with actual physical platform. The simulation yields effective outcomes with 96.94% accuracy for testing stage while maintaining error and loss values of 0.194 and 0.183 respectively. The proposed interface gives consistent results for teaching application in real time changing environment by outperforming existing methods with an accuracy improvement of 13.4

Joint entity and relation extraction is to detect entity and relation using a single model. In this paper, we present a novel unified joint extraction model which directly tags entity and relation labels according to a query word position p, i.e., detecting entity at p, and identifying entities at other positions that have relationship with the former. To this end, we first design a tagging scheme to generate n tag sequences for an n-word sentence. Then a position-attention mechanism is introduced to produce different sentence representations for every query position to model these n tag sequences. In this way, our method can simultaneously extract all entities and their type, as well as all overlapping relations. Experiment results show that our framework performances significantly better on extracting overlapping relations as well as detecting long-range relation, and thus we achieve state-of-the-art performance on two public datasets.

Surface waves are advantageous for mapping seismic structures of permafrost, in which irregular velocity gradients are common and thus the effectiveness of refraction methods are limited. Nevertheless, the complex velocity structures that are common in permafrost environments often yield unusual dispersion spectra, in which higher-order and leaky modes are dominant. Such unusual dispersion spectra were prevalent in the multichannel surface-wave data acquired from our permafrost study site at Barrow, Alaska. Owing to the difficulties in picking and identifying dispersion curves from these dispersion spectra, conventional surface-wave inversion methods become problematic to apply. To overcome these difficulties, we adopted a full-wavefield method to invert for velocity models that can best fit the dispersion spectra instead of the dispersion curves. The inferred velocity models were consistent with collocated electric resistivity results and with subsequent confirmation cores, which indicated the reliability of the recovered seismic structures. The results revealed embedded low-velocity zones underlying the ice-rich permafrost at our study site — an unexpected feature considering the low ground temperatures of [Formula: see text] to [Formula: see text]. The low velocities in these zones ([Formula: see text] lower than the overlying ice-rich permafrost) were most likely caused by saline pore-waters that prevent the ground from freezing, and the resultant velocity structures are vivid examples of complex subsurface properties in permafrost terrain. We determined that full-wavefield inversion of surface waves, although carrying higher computational costs than conventional methods, can be an effective tool for delineating the seismic structures of permafrost.

Several recent studies have demonstrated that Distributed Acoustic Sensing (DAS) can utilize existing subsurface telecom fiber (i.e. dark fiber) for high quality seismic measurements. Researchers to date have shown that this sensing combination, coupled to ambient noise interferometry techniques, can effectively image the shallow subsurface (< 30 m) using vehicle and infrastructure noise (f = 8 - 30 Hz). We present the first long-offset surface wave inversion study targeting deeper (⁓ 500 m) structure using DAS and dark fiber. This study utilizes a previously acquired dataset collected on a 23 km fiber section between West Sacramento and Woodland, CA, part of the DOE Energy Science Network (ESnet). By targeting noise generated by a co-linear rail line, broadband and rich in low frequencies (down to f=1 Hz), and long array offsets, we generate high-quality interferometric gathers suitable for inversion. Subsequent surface wave inversions using a multimode Monte Carlo (MC) sampling algorithm are consistent with geology and available confirmatory datasets derived from co-located sonic logs. The relatively sparse confirmatory data demonstrates, by comparison, the utility of the high spatial sampling provided by DAS. These results open the door to larger regional DAS studies targeting deeper targets but with resolutions higher than those afforded by the use of persistent low frequency (f

This paper adopts a flow-punched technology for laminated composite which combines jet-flow and carbon fiber piercing technology. The jet-flow-based preform forming experiment system is constructed, and jet flow technology is used to prepare the interlaminar reinforced carbon fiber composite materials. The reinforced carbon fiber bundle is shot into the microstructure of the laminated composite in all directions and laminated carbon fiber becomes an entire, and then it is treated by vacuum and curing process. This paper provides a technological approach to improve the quality of the laminated composite preform.

A filtering algorithm and direction identification method are presented for the positioning system of the mid-speed maglev train. Considering the special structure of the mid-speed maglev train, the ground position estimation method is adopted for its traction system. As the train is running, the induction loop-cable receives the signal sent by the on-board antenna to detect the position and direction of the train. But the height of the on-board antenna relative to the loop-cable is highly vulnerable to the change of the suspension height and the magnetic field produced by the traction during traveling, which may lead to amplitude fluctuation of the received signal. Consequently, the position estimation may be inaccurate. Therefore, a discrete second-order nonlinear trackdifferentiator is proposed based on the boundary characteristic curves, and the new differentiator could also extract the running direction of the train for the traction system. The experimental results show that the tracking differentiator can effectively filter out the signal interference and can provide accurate direction signal.

Saline permafrost is sensitive to thermal disturbances and is prone to subsidence, which renders it a major source of geohazard in Arctic coastal environments. Seismic methods could be used to map and monitor saline permafrost at scales of geotechnical interests because of the ice-content dependencies of seismic properties. We have developed a comprehensive study of the ultrasonic P-wave properties (i.e., velocity and attenuation) of synthetic saline permafrost samples for a range of salinities and temperatures, and measurements conducted on a fine-grained permafrost core obtained from Barrow, Alaska. The resulting data consist of P-wave properties presented as functions of temperature and salinity. Notable observations include the following: P-wave velocities showed marked reductions in the presence of dissolved salts and complex variations resulting from the water-to-ice phase transitions; strong P-wave attenuation was present in the temperature intervals in which the samples were partially frozen. When presented as functions of ice saturation, the data sets lead us to two key findings: (1) neither a purely cementing nor a purely pore-filling model of the pore-scale distributions of ice could adequately fit the observed velocity data and (2) although the velocities increase monotonically with increasing ice saturations, P-wave attenuation reaches a maximum at intermediate ice saturations—contrary to the ordinary expectation of decreasing attenuation with increasing velocities. The observed ice-content dependencies of P-wave properties, along with the implications on the probable pore-scale distributions of ice, provide a valuable basis for rock-physics modeling, which in turn could facilitate seismic characterizations of saline permafrost.

Global climate change has resulted in a warmer Arctic, with projections indicating accelerated modifications to permafrost in the near future. The thermal, hydrological, and mechanical physics of permafrost thaw have been hypothesized to couple in a complex fashion but data collection efforts to study these feedbacks in the field have been limited. As a result, laboratory and numerical models have largely outpaced field calibration datasets. We present the design, execution, and initial results from the first decameter-scale controlled thawing experiment, targeting coupled thermal/mechanical response, particularly the temporal sequence of surface subsidence relative to permafrost degradation at depth. The warming test was conducted in Fairbanks, AK, and utilized an array of in-ground heaters to induce thaw of a ~11 × 13 × 1.5 m soil volume over 63 days. The 4-D temperature evolution demonstrated that the depth to permafrost lowered 1 m during the experiment. The resulting thaw-induced surface deformation was ~10 cm as observed using a combination of measurement techniques. Surface deformation occurred over a smaller spatial domain than the full thawed volume, suggesting that gradients in cryotexture and ice content were significant. Our experiment provides the first large field calibration dataset for multiphysics thaw models.

We show how to estimate the fluid permeability changes due to accumulated biopolymer within the pore space of a granular material using laboratory measurements of overall permeability, together with various well-known quantitative measures (e.g., porosity, specific surface area, and formation factor) of the granular medium microstructure. The main focus of the paper is on mutual validation of existing theory and a synthesis of new experimental results. We find that the theory and data are in good agreement within normal experimental uncertainties. We also establish quantitative empirical relationships between seismic and/or acoustic attenuation and overall permeability for these same systems.

© International Union of Crystallography, 2017. Continuous improvements at X-ray imaging beamlines at synchrotron light sources have made dynamic synchrotron X-ray micro-computed tomography (SXR-μCT) experiments more routinely available to users, with a rapid increase in demand given its tremendous potential in very diverse areas. In this work a survey of five different four-dimensional SXR-μCT experiments is presented, examining five different parameters linked to the evolution of the investigated system, and tackling problems in different areas in earth sciences. SXR-μCT is used to monitor the microstructural evolution of the investigated sample with the following variables: (i) high temperature, observing in situ oil shale pyrolysis; (ii) low temperature, replicating the generation of permafrost; (iii) high pressure, to study the invasion of supercritical CO2in deep aquifers; (iv) uniaxial stress, to monitor the closure of a fracture filled with proppant, in shale; (v) reactive flow, to observe the evolution of the hydraulic properties in a porous rock subject to dissolution. For each of these examples, it is shown how dynamic SXR-μCT was able to provide new answers to questions related to climate and energy studies, highlighting the significant opportunities opened recently by the technique.Recent developments in in situ synchrotron X-ray micro-computed tomography allow novel time-resolved experiments. Five different dynamic micro-computed tomography experiments addressing carbon sequestration, permafrost evolution and unconventional oil recovery topics are presented.

© The Authors. Published by the Society of Exploration Geophysicists. To better understand the relationship between P-wave velocities and ice content in saturated, unconsolidated saline permafrost, we constructed an effective-medium model based upon ultrasonic P-wave data that were obtained from earlier laboratory studies. The model uses a two-end-member mixing approach in which an ice-filled, fully frozen end member and a water-filled, fully unfrozen end member are mixed together to form the effective medium of partially frozen sediments. This mixing approach has two key advantages: (1) It does not require parameter tuning of the mixing ratios, and (2) it inherently assumes mixed pore-scale distributions of ice that consist of frame-strengthening (i.e., cementing and/or loadbearing) ice and pore-filling ice. The model-predicted P-wave velocities agree well with our laboratory data, demonstrating the effectiveness of the model for quantitatively inferring ice content from P-wave velocities. The modeling workflow is simple and is largely free of calibration parameters -attributes that ease its application in interpreting field data sets.

The diets of the wolf Canis lupus, red fox Vulpes vulpes and raccoon dog Nyctereutes ussurienusis Matschie were studied in the grassland of eastern Inner Mongolia from August to October in 2007 and from March to July in 2008. Feces were collected from dens and latrines. The frequency of occurrence and the dry weight of the remains of each food item in the feces were calculated. Livestock (50.65% frequency of occurrence) constituted the bulk of the wolf diet, while small rodents (76.31% frequency of occurrence) were most frequently eaten by the foxes. Small rodents (22.69% frequency of occurrence) were important to the raccoon dogs but they also frequently consumed birds (39.81% frequency of occurrence) and insects (26.39% frequency of occurrence). The wolf was the most omnivorous and the red fox was the least omnivorous of these three kinds of canidae according to the diversity index. The food niches of the wolf and the red fox overlapped more than that of the raccoon dog and other species. These three kinds of canidae shared many resources and consequently competition occurred to them. However, their diets also differed to some extent which helped them to avoid competition. Furthermore, raccoon dogs were dormant in winter when food was scarce, which may be the reason why all these species could coexist in a rather unproductive grassland.

Summary We present results from an intermediate scale field experiment conducted in December 2014, evaluating the use of Distributed Acoustic Sensing (DAS) for recording ambient noise generated by infrastructure use; the future aim of our effort is to utilize ambient noise for real-time geotechnical evaluation of soils beneath active infrastructure. We present details of the installation, recording comparisons of 4 selected DAS cables, and a noise comparison between DAS and classical 3C geophones. We conclude by showing preliminary examples of ambient noise interferometry using passive data acquired with DAS vs. 3C geophones.

Distributed acoustic sensing (DAS) is a relatively recent development in the use of fiber-optic cable for measurement of ground motion. Discrete fiber-optic sensors, typically using a Bragg diffraction grating, have been in research and development and field testing for more than 15 years with geophysical applications at least 12 years old (Bostick, 2000, and summary in Keul et al., 2005). However, developments in recent years have sought to remove the need for point sensors by using the fiber cable itself as a sensor (Mestayer et al., 2011; Miller et al., 2012).

Seismic methods have the benefit of being noninvasive while providing continuous field-scale (hundreds of meters) information on subsurface characteristics of permafrost-affected soils. Imaging approaches based on surface wave propagation (e.g. MASW) are effective when characterizaing near-surface permafrost alteration (e.g. active zone freeze/thaw cycles) for at least two reasons: (1) energetic propagations within the top 10s of meters of the subsurface; (2) its direct indications on shear wave velocity, a sensitive indicator of soil matrix properties. We present a four-phase rock physics model developed for mapping frozen soil material properties to seismic observables. We predict seasonal variations in Pand S-wave velocities from the rock physics model based on existing in situ ground temperature measurements. We also conduct numerical simulations of seismic wave propagations based upon velocity models derived from rock physics model predictions. Surface wave dispersion analysis results generated from the resultant synthetic seismograms show that seismic methods, especially surface-wave-based approaches, are very promising approaches for delineating subsurface features in permafrost environments such as active layer thickness (ALT) variations, ice saturation, unfrozen water content, and soil texture, etc.

Summary We have deployed a novel permanent monitoring system at the Australian CO2CRC Otway Site that includes a surface and borehole distributed acoustic sensing (DAS) network with orbital vibrator (rotary) surface seismic sources. DAS is an emerging technology for performing seismic acquisition based on optical interferometric techniques, which allows for data collection with a wide spatial aperture and high temporal resolution using commercially available telecommunications fibres. DAS sensitivity currently lags behind conventional discrete geophone and hydrophone sensor technologies. Our implementation of surface rotary seismic sources is based on open-loop controlled asynchronous motors. This avoids the complexity of feedback loops for phase control, instead using deconvolution of the source function as measured by a shallow source-monitor sensor. Initial data analysis shows that the amount of energy available from long source sweeps overcomes limitations in DAS sensitivity. The combination of relatively inexpensive but powerful permanent surface sources with permanent DAS deployment in an areal array provides a new paradigm for time-lapse seismic monitoring. The methodology we describe has broad applicability for long-term reservoir surveillance, with time-lapse change sensitive to many subsurface properties.